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alhparsa/
qwen35-extract-tsv-v2

Name: qwen35-extract-tsv-v2
Availability: InStock

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qwen35-extract-tsv-v1

Selective full-FT of Qwen3.5-9B for medical admission-fact extraction from document page images. Output is compact TSV (CTX line + 6 TAB-separated columns/fact), not JSON.

Quality: ~98–100% recall / ~100% precision post-dedup (image-grounded judges). Speed: 4.4–4.9 s/page with the DFlash drafter on 2×H100 (see below).

Architecture: hybrid GatedDeltaNet (24 GDN + 8 full-attn) + vision tower + MTP head. The arch drives the gotchas below — read them before serving.

Serve (vLLM, recommended)

bash

vllm serve alhparsa/qwen35-extract-tsv-v1 \
  --speculative-config '{"method":"dflash","model":"alhparsa/qwen35-9b-dflash","num_speculative_tokens":15}' \
  --max-model-len 32768 \
  --attention-backend flash_attn \
  --max-num-batched-tokens 32768 \
  --mm-processor-kwargs '{"max_pixels": 1003520}' \
  --default-chat-template-kwargs '{"enable_thinking": false}'

The --speculative-config is lossless speedup only (the drafter proposes tokens, this model verifies them — identical output). Drop it to serve ~2× slower with no other change. Run one replica per GPU and round-robin requests for best throughput.

Decode params — must match training

temperature 0.7 top_p 0.8 top_k 20 repetition_penalty 1.08 seed 0

Greedy / low-temp measurably hurts recall. Do not change these.

Message format

System: the short system prompt (short_sys.txt) with {today_date} filled to today (ISO).
User: [Available tags list] + "Previous context before this window:\n\n", then per page "Page N\n\n" + the page image, then "Extract all facts from these consecutive pages."
The model only emits tags present in the Available tags list you pass in the user message.
Patient identity (name/MRN/DOB/CSN) comes out on the CTX first line, not as fact rows.

Sample input / output

Real held-out example (an Occupational Therapy evaluation page, mid-document window). Page image elided.

Input messages:

json

[
  {"role": "system", "content": "% You are an AI specialized in extracting ... Today's date is: 2026-06-18\n% ... (short_sys.txt, full text — the 6-column TSV contract)"},
  {"role": "user", "content": [
    {"type": "text", "text": "Available tags:\nMDS Tags:\n- mds_a_id_info ... - mds_q_participation\nDocument Type Tags:\n- med_diag, allergy, vital, lab_result, evaluation, therapy, progress_note, care_plan, medication, physical_exam ...\n\nPrevious context before this window:\nActive Service Date: 2026-05-17; source_label: \"Today's Date\". This page continues the Occupational Therapy Evaluation. It includes AM-PAC Daily Activity scores, Transfers (deferred due to pain), Balance, Coordination, Functional Cognition (Intact/Alert), ROM, Strength ...\n\n"},
    {"type": "text", "text": "Page 40\n\n"},
    {"type": "image_url", "image_url": {"url": "data:image/png;base64,<...page...>"}},
    {"type": "text", "text": "Extract all facts from these consecutive pages."}
  ]}
]

Output (TSV — CTX line, then page⇥fact⇥tags⇥temporal_date⇥temporal_text⇥confidence):

CTX: Active Service Date: 2026-05-17; source_label: "Today's Date". This page concludes the Occupational Therapy Evaluation with short-term goals for transfers, dressing, and bed mobility, classifies the evaluation as high complexity, and includes ADL flowsheet data and a Last Skin Assessment dated 05/18/2026.
40	Favorable for Outcome: PLOF;Motivated;Intact Cognition	evaluation,therapy	2026-05-17	5/17/2026	-
40	Barriers to Outcome: Comorbidities;Lives Alone;Decreased Activity Tolerance;Decreased UE Fxnl Use;Pain	evaluation,therapy	2026-05-17	5/17/2026	-
40	Problem List: Decreased ADL status;Decreased UE strength;Decreased UE ROM;Decreased LE ROM;Decreased LE strength;Decreased activity tolerance;Decreased transfer ability;Decreased coordination;Impaired functional mobility;Impaired balance;Impaired gait;Pain;Decreased high-level ADLs	evaluation,therapy	2026-05-17	5/17/2026	-
40	Rehab Potential: Good	evaluation,therapy	2026-05-17	5/17/2026	-
40	OT Priority: 3 SAT 5/16; FBR	evaluation,therapy	2026-05-17	5/17/2026	-
40	OT Frequency: 1-2x/wk	evaluation,therapy	2026-05-17	5/17/2026	-

Notes: the Previous context block carries the prior window's CTX so facts spanning a page break aren't lost; page is the real source page (40); temporal_date (ISO) and temporal_text (as written) are populated from the active service date; tags come only from the Available tags list. Patient identity (when present) lands on the CTX line, not as fact rows.

Plain transformers (sanity check, no vLLM/drafter)

See hf_infer_sample.py in the training repo — loads via AutoModelForImageTextToText, max_pixels=1003520, the decode params above. No drafter (vLLM-only), no PDF render/windowing/dedup.

Serving gotchas (each cost a debug round)

Never enable ngram/prompt-lookup speculation — GatedDeltaNet state can't roll back rejected drafts → silent corruption. DFlash/MTP only.
Keep --mm-processor-kwargs '{"max_pixels": 1003520}' — without it images are processed at native res (off-distribution + slow). preprocessor_config.json is included here.
The 15 mtp.* tensors are required for speculative decode; they are present in this checkpoint. If you re-merge/requant, re-graft them or spec decode breaks.
Prefix caching auto-disables on hybrid models; attention block size is forced for mamba page alignment — expected, not a bug.
PyPI vLLM wheel may need CUDA-13 runtime libs on LD_LIBRARY_PATH.

Drafter

alhparsa/qwen35-9b-dflash is a mirror of public z-lab/Qwen3.5-9B-DFlash. It was trained on stock Qwen3.5-9B, not recalibrated to this fine-tune, so acceptance is a bit below z-lab's headline — still a clear win.

Recommended pipeline (prod recall)

Render PDF pages at 2.0 zoom → 3-page windows, stride 2 (1-page overlap) → concurrent requests round-robin across replicas → parse TSV → extract identity from CTX line → reseed-retry any window returning <5 facts → union → semantic dedup. Single-window inference under-recalls on multi-page docs.

alhparsa/qwen35-extract-tsv-v2